Pandas Profiling Report

Dataset statistics

Number of variables	12
Number of observations	785456
Missing cells	1146981
Missing cells (%)	12.2%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	71.9 MiB
Average record size in memory	96.0 B

Variable types

Numeric	6
DateTime	3
Text	3

Alerts

`OwnerDisplayName` has 772004 (98.3%) missing values	Missing
`LastEditDate` has 374977 (47.7%) missing values	Missing
`Score` is highly skewed (γ1 = 32.66621385)	Skewed
`ViewCount` is highly skewed (γ1 = 128.8200658)	Skewed
`Id` has unique values	Unique
`Score` has 441895 (56.3%) zeros	Zeros
`AnswerCount` has 178726 (22.8%) zeros	Zeros
`CommentCount` has 302229 (38.5%) zeros	Zeros

Reproduction

Analysis started	2023-10-15 18:10:13.948286
Analysis finished	2023-10-15 18:13:56.807525
Duration	3 minutes and 42.86 seconds
Software version	ydata-profiling vv4.6.0
Download configuration	config.json

Unnamed: 0
Real number (ℝ)

Distinct	49998
Distinct (%)	6.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	21354.159

Minimum	0
Maximum	49997
Zeros	21
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	6.0 MiB

Quantile statistics

Minimum	0
5-th percentile	1818
Q1	9126
median	20569
Q3	32778
95-th percentile	43524
Maximum	49997
Range	49997
Interquartile range (IQR)	23652

Descriptive statistics

Standard deviation	13517.781
Coefficient of variation (CV)	0.633028
Kurtosis	-1.163667
Mean	21354.159
Median Absolute Deviation (MAD)	11777
Skewness	0.1718686
Sum	1.6772753 × 10¹⁰
Variance	1.827304 × 10⁸
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1313	22	< 0.1%
4681	22	< 0.1%
4691	22	< 0.1%
4690	22	< 0.1%
4689	22	< 0.1%
4688	22	< 0.1%
4687	22	< 0.1%
4686	22	< 0.1%
4685	22	< 0.1%
4684	22	< 0.1%
Other values (49988)	785236	> 99.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	21	< 0.1%
1	21	< 0.1%
2	21	< 0.1%
3	21	< 0.1%
4	21	< 0.1%
5	21	< 0.1%
6	21	< 0.1%
7	21	< 0.1%
8	21	< 0.1%
9	21	< 0.1%

Value	Count	Frequency (%)
49997	1	< 0.1%
49996	1	< 0.1%
49995	1	< 0.1%
49994	1	< 0.1%
49993	1	< 0.1%
49992	1	< 0.1%
49991	1	< 0.1%
49990	1	< 0.1%
49989	1	< 0.1%
49988	1	< 0.1%

Id
Real number (ℝ)

UNIQUE

Distinct	785456
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	71059652

Minimum	64627531
Maximum	77253066
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	6.0 MiB

Quantile statistics

Minimum	64627531
5-th percentile	65285958
Q1	67899742
median	71146176
Q3	74263733
95-th percentile	76625143
Maximum	77253066
Range	12625535
Interquartile range (IQR)	6363991.2

Descriptive statistics

Standard deviation	3640996.9
Coefficient of variation (CV)	0.051238598
Kurtosis	-1.204849
Mean	71059652
Median Absolute Deviation (MAD)	3174826.5
Skewness	-0.049631619
Sum	5.581423 × 10¹³
Variance	1.3256859 × 10¹³
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
77253066	1	< 0.1%
68289593	1	< 0.1%
68288262	1	< 0.1%
68288283	1	< 0.1%
68288285	1	< 0.1%
68288292	1	< 0.1%
68288300	1	< 0.1%
68288316	1	< 0.1%
68288355	1	< 0.1%
68288390	1	< 0.1%
Other values (785446)	785446	> 99.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
64627531	1	< 0.1%
64627553	1	< 0.1%
64627555	1	< 0.1%
64627576	1	< 0.1%
64627590	1	< 0.1%
64627602	1	< 0.1%
64627612	1	< 0.1%
64627617	1	< 0.1%
64627630	1	< 0.1%
64627639	1	< 0.1%

Value	Count	Frequency (%)
77253066	1	< 0.1%
77253065	1	< 0.1%
77253053	1	< 0.1%
77253022	1	< 0.1%
77253020	1	< 0.1%
77253005	1	< 0.1%
77252996	1	< 0.1%
77252992	1	< 0.1%
77252991	1	< 0.1%
77252989	1	< 0.1%

CreationDate
Date

Distinct	781082
Distinct (%)	99.4%
Missing	0
Missing (%)	0.0%
Memory size	6.0 MiB

Minimum	2020-11-01 00:03:26
Maximum	2023-10-08 09:37:48

Histogram

Histogram with fixed size bins (bins=50)

Score
Real number (ℝ)

SKEWED ZEROS

Distinct	130
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.43050661

Minimum	-16
Maximum	286
Zeros	441895
Zeros (%)	56.3%
Negative	76732
Negative (%)	9.8%
Memory size	6.0 MiB

Quantile statistics

Minimum	-16
5-th percentile	-1
Q1	0
median	0
Q3	1
95-th percentile	2
Maximum	286
Range	302
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.9055843
Coefficient of variation (CV)	4.4263765
Kurtosis	2684.696
Mean	0.43050661
Median Absolute Deviation (MAD)	0
Skewness	32.666214
Sum	338144
Variance	3.6312517
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	441895	56.3%
1	177381	22.6%
2	55080	7.0%
-1	50235	6.4%
3	18115	2.3%
-2	17188	2.2%
4	7108	0.9%
-3	6279	0.8%
5	3257	0.4%
-4	2050	0.3%
Other values (120)	6868	0.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
-16	2	< 0.1%
-14	1	< 0.1%
-13	1	< 0.1%
-12	4	< 0.1%
-11	1	< 0.1%
-10	10	< 0.1%
-9	21	< 0.1%
-8	39	< 0.1%
-7	91	< 0.1%
-6	202	< 0.1%

Value	Count	Frequency (%)
286	1	< 0.1%
223	1	< 0.1%
217	1	< 0.1%
197	1	< 0.1%
196	1	< 0.1%
189	1	< 0.1%
186	1	< 0.1%
175	1	< 0.1%
171	3	< 0.1%
169	1	< 0.1%

ViewCount
Real number (ℝ)

SKEWED

Distinct	10886
Distinct (%)	1.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	481.79102

Minimum	2
Maximum	1156519
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	6.0 MiB

Quantile statistics

Minimum	2
5-th percentile	26
Q1	53
median	122
Q3	375
95-th percentile	1624
Maximum	1156519
Range	1156517
Interquartile range (IQR)	322

Descriptive statistics

Standard deviation	2842.4085
Coefficient of variation (CV)	5.8996711
Kurtosis	39576.622
Mean	481.79102
Median Absolute Deviation (MAD)	86
Skewness	128.82007
Sum	3.7842564 × 10⁸
Variance	8079286.4
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
41	6383	0.8%
40	6374	0.8%
37	6340	0.8%
38	6334	0.8%
36	6329	0.8%
39	6327	0.8%
43	6308	0.8%
42	6308	0.8%
35	6302	0.8%
44	6204	0.8%
Other values (10876)	722247	92.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
2	1	< 0.1%
3	6	< 0.1%
4	11	< 0.1%
5	38	< 0.1%
6	79	< 0.1%
7	139	< 0.1%
8	220	< 0.1%
9	328	< 0.1%
10	482	0.1%
11	642	0.1%

Value	Count	Frequency (%)
1156519	1	< 0.1%
567907	1	< 0.1%
433844	1	< 0.1%
352483	1	< 0.1%
343214	1	< 0.1%
324098	1	< 0.1%
319989	1	< 0.1%
253962	1	< 0.1%
236844	1	< 0.1%
235719	1	< 0.1%

AnswerCount
Real number (ℝ)

ZEROS

Distinct	24
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.1092614

Minimum	0
Maximum	25
Zeros	178726
Zeros (%)	22.8%
Negative	0
Negative (%)	0.0%
Memory size	6.0 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	1
median	1
Q3	1
95-th percentile	3
Maximum	25
Range	25
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.92280776
Coefficient of variation (CV)	0.83191193
Kurtosis	9.5366007
Mean	1.1092614
Median Absolute Deviation (MAD)	0
Skewness	1.6887528
Sum	871276
Variance	0.85157417
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=24)

Value	Count	Frequency (%)
1	419827	53.5%
0	178726	22.8%
2	133175	17.0%
3	37986	4.8%
4	10774	1.4%
5	3320	0.4%
6	991	0.1%
7	342	< 0.1%
8	138	< 0.1%
9	65	< 0.1%
Other values (14)	112	< 0.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	178726	22.8%
1	419827	53.5%
2	133175	17.0%
3	37986	4.8%
4	10774	1.4%
5	3320	0.4%
6	991	0.1%
7	342	< 0.1%
8	138	< 0.1%
9	65	< 0.1%

Value	Count	Frequency (%)
25	1	< 0.1%
23	1	< 0.1%
22	3	< 0.1%
20	1	< 0.1%
19	1	< 0.1%
18	3	< 0.1%
17	4	< 0.1%
16	1	< 0.1%
15	8	< 0.1%
14	5	< 0.1%

Title
Text

Distinct	785350
Distinct (%)	> 99.9%
Missing	0
Missing (%)	0.0%
Memory size	6.0 MiB

Length

Max length	150
Median length	124
Mean length	61.223578
Min length	15

Characters and Unicode

Total characters	48088427
Distinct characters	424
Distinct categories	25 ?
Distinct scripts	14 ?
Distinct blocks	34 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	785252 ?
Unique (%)	> 99.9%

Sample

1st row	How to solve create next app npm run build placing href with _next instead of .next in the html files from the server?
2nd row	Time series prediction code fails to run in an iterative loop, but works when run out of loop
3rd row	Two way communication between two Processes python
4th row	Plotting with subplots in a loop in one figure
5th row	Adjust the edge points of a rectangular shaped contour

Value	Count	Frequency (%)
to	334970	4.2%
in	309066	3.8%
a	277256	3.4%
how	204769	2.5%
python	182503	2.3%
the	164140	2.0%
of	146085	1.8%
with	125800	1.6%
and	104765	1.3%
from	88303	1.1%
Other values (162315)	6128583	76.0%

Most occurring characters

Value	Count	Frequency (%)
	7280658	15.1%
e	3891182	8.1%
t	3573040	7.4%
o	3271964	6.8%
n	3162230	6.6%
a	2984655	6.2%
i	2839037	5.9%
r	2393761	5.0%
s	2109689	4.4%
l	1609555	3.3%
Other values (414)	14972656	31.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	37430779	77.8%
Space Separator	7280738	15.1%
Uppercase Letter	2046524	4.3%
Other Punctuation	714206	1.5%
Decimal Number	209307	0.4%
Open Punctuation	98027	0.2%
Close Punctuation	97254	0.2%
Dash Punctuation	96595	0.2%
Connector Punctuation	67503	0.1%
Math Symbol	28585	0.1%
Other values (15)	18909	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	3891182	10.4%
t	3573040	9.5%
o	3271964	8.7%
n	3162230	8.4%
a	2984655	8.0%
i	2839037	7.6%
r	2393761	6.4%
s	2109689	5.6%
l	1609555	4.3%
d	1284502	3.4%
Other values (136)	10311164	27.5%

Uppercase Letter

Value	Count	Frequency (%)
P	234200	11.4%
H	198137	9.7%
I	168858	8.3%
S	152000	7.4%
C	133356	6.5%
R	132360	6.5%
D	110405	5.4%
E	99937	4.9%
A	97021	4.7%
T	95367	4.7%
Other values (58)	624883	30.5%

Other Punctuation

Value	Count	Frequency (%)
?	191237	26.8%
'	126090	17.7%
.	119840	16.8%
:	96260	13.5%
,	72589	10.2%
"	56775	7.9%
/	32747	4.6%
*	3446	0.5%
\	3436	0.5%
%	3174	0.4%
Other values (26)	8612	1.2%

Math Symbol

Value	Count	Frequency (%)
=	9460	33.1%
+	7414	25.9%
>	5110	17.9%
<	4160	14.6%
\|	1977	6.9%
~	330	1.2%
×	31	0.1%
→	21	0.1%
−	18	0.1%
≤	11	< 0.1%
Other values (19)	53	0.2%

Other Symbol

Value	Count	Frequency (%)
°	29	37.2%
�	9	11.5%
™	4	5.1%
®	4	5.1%
¦	2	2.6%
│	2	2.6%
✖	2	2.6%
▸	2	2.6%
👩	2	2.6%
💻	2	2.6%
Other values (18)	20	25.6%

Nonspacing Mark

Value	Count	Frequency (%)
̶	8	22.9%
̃	3	8.6%
️	3	8.6%
̂	2	5.7%
゙	2	5.7%
̄	2	5.7%
͡	2	5.7%
︁	1	2.9%
ं	1	2.9%
्	1	2.9%
Other values (10)	10	28.6%

Other Letter

Value	Count	Frequency (%)
ه	9	27.3%
º	5	15.2%
し	4	12.1%
글	1	3.0%
ǃ	1	3.0%
한	1	3.0%
व	1	3.0%
क	1	3.0%
ष	1	3.0%
य	1	3.0%
Other values (8)	8	24.2%

Decimal Number

Value	Count	Frequency (%)
2	44640	21.3%
0	38859	18.6%
1	38492	18.4%
3	30877	14.8%
4	16869	8.1%
5	13212	6.3%
6	8874	4.2%
8	6792	3.2%
9	5586	2.7%
7	5097	2.4%
Other values (6)	9	< 0.1%

Open Punctuation

Value	Count	Frequency (%)
(	86858	88.6%
[	9647	9.8%
{	1488	1.5%
（	15	< 0.1%
【	9	< 0.1%
„	7	< 0.1%
‚	1	< 0.1%
「	1	< 0.1%
〔	1	< 0.1%

Close Punctuation

Value	Count	Frequency (%)
)	86434	88.9%
]	9413	9.7%
}	1381	1.4%
）	13	< 0.1%
】	9	< 0.1%
》	2	< 0.1%
」	1	< 0.1%
〕	1	< 0.1%

Currency Symbol

Value	Count	Frequency (%)
$	1149	96.9%
€	23	1.9%
£	11	0.9%
¢	1	0.1%
₹	1	0.1%
¤	1	0.1%

Other Number

Value	Count	Frequency (%)
²	19	73.1%
½	2	7.7%
³	2	7.7%
₀	1	3.8%
₁	1	3.8%
⁴	1	3.8%

Dash Punctuation

Value	Count	Frequency (%)
-	96350	99.7%
–	142	0.1%
—	90	0.1%
‑	12	< 0.1%
―	1	< 0.1%

Space Separator

Value	Count	Frequency (%)
	7280658	> 99.9%
	75	< 0.1%
	4	< 0.1%
	1	< 0.1%

Modifier Symbol

Value	Count	Frequency (%)
`	14383	95.5%
^	477	3.2%
´	192	1.3%
¯	1	< 0.1%

Final Punctuation

Value	Count	Frequency (%)
’	820	64.9%
”	432	34.2%
»	9	0.7%
›	2	0.2%

Initial Punctuation

Value	Count	Frequency (%)
‘	480	52.3%
“	434	47.3%
«	4	0.4%

Format

Value	Count	Frequency (%)
	250	96.2%
‍	7	2.7%
‌	3	1.2%

Spacing Mark

Value	Count	Frequency (%)
ा	2	50.0%
ि	1	25.0%
ो	1	25.0%

Modifier Letter

Value	Count	Frequency (%)
ˆ	2	66.7%
ⁿ	1	33.3%

Private Use

Value	Count	Frequency (%)
􏰁	1	50.0%
􏰂	1	50.0%

Connector Punctuation

Value	Count	Frequency (%)
_	67503	100.0%

Control

Value	Count	Frequency (%)
	45	100.0%

Enclosing Mark

Value	Count	Frequency (%)
⃣	2	100.0%

Line Separator

Value	Count	Frequency (%)
	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	39476958	82.1%
Common	8611082	17.9%
Cyrillic	214	< 0.1%
Greek	77	< 0.1%
Inherited	41	< 0.1%
Arabic	19	< 0.1%
Devanagari	15	< 0.1%
Hebrew	6	< 0.1%
Hiragana	4	< 0.1%
Han	4	< 0.1%
Other values (4)	7	< 0.1%

Most frequent character per script

Common

Value	Count	Frequency (%)
	7280658	84.5%
?	191237	2.2%
'	126090	1.5%
.	119840	1.4%
-	96350	1.1%
:	96260	1.1%
(	86858	1.0%
)	86434	1.0%
,	72589	0.8%
_	67503	0.8%
Other values (180)	387263	4.5%

Latin

Value	Count	Frequency (%)
e	3891182	9.9%
t	3573040	9.1%
o	3271964	8.3%
n	3162230	8.0%
a	2984655	7.6%
i	2839037	7.2%
r	2393761	6.1%
s	2109689	5.3%
l	1609555	4.1%
d	1284502	3.3%
Other values (114)	12357343	31.3%

Cyrillic

Value	Count	Frequency (%)
С	28	13.1%
о	22	10.3%
а	13	6.1%
в	13	6.1%
н	12	5.6%
е	12	5.6%
к	10	4.7%
с	10	4.7%
т	10	4.7%
и	9	4.2%
Other values (22)	75	35.0%

Greek

Value	Count	Frequency (%)
λ	10	13.0%
μ	8	10.4%
π	8	10.4%
β	7	9.1%
α	7	9.1%
θ	6	7.8%
σ	4	5.2%
δ	3	3.9%
Σ	3	3.9%
ε	2	2.6%
Other values (16)	19	24.7%

Inherited

Value	Count	Frequency (%)
̶	8	19.5%
‍	7	17.1%
‌	3	7.3%
̃	3	7.3%
️	3	7.3%
̂	2	4.9%
⃣	2	4.9%
゙	2	4.9%
̄	2	4.9%
͡	2	4.9%
Other values (7)	7	17.1%

Devanagari

Value	Count	Frequency (%)
ा	2	13.3%
ि	1	6.7%
व	1	6.7%
क	1	6.7%
ष	1	6.7%
य	1	6.7%
ो	1	6.7%
ं	1	6.7%
ख	1	6.7%
्	1	6.7%
Other values (4)	4	26.7%

Arabic

Value	Count	Frequency (%)
ه	9	47.4%
٢	3	15.8%
٠	2	10.5%
١	1	5.3%
٥	1	5.3%
٤	1	5.3%
ۜ	1	5.3%
ۣ	1	5.3%

Han

Value	Count	Frequency (%)
坐	1	25.0%
标	1	25.0%
锛	1	25.0%
稳	1	25.0%

Hangul

Value	Count	Frequency (%)
글	1	50.0%
한	1	50.0%

Thai

Value	Count	Frequency (%)
็	1	50.0%
๖	1	50.0%

Unknown

Value	Count	Frequency (%)
􏰁	1	50.0%
􏰂	1	50.0%

Hebrew

Value	Count	Frequency (%)
׳	6	100.0%

Hiragana

Value	Count	Frequency (%)
し	4	100.0%

Georgian

Value	Count	Frequency (%)
ღ	1	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	48083973	> 99.9%
Punctuation	2733	< 0.1%
None	1204	< 0.1%
Cyrillic	214	< 0.1%
Math Operators	64	< 0.1%
Math Alphanum	50	< 0.1%
Arabic	27	< 0.1%
Currency Symbols	24	< 0.1%
Arrows	23	< 0.1%
Diacriticals	21	< 0.1%
Other values (24)	94	< 0.1%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	7280658	15.1%
e	3891182	8.1%
t	3573040	7.4%
o	3271964	6.8%
n	3162230	6.6%
a	2984655	6.2%
i	2839037	5.9%
r	2393761	5.0%
s	2109689	4.4%
l	1609555	3.3%
Other values (86)	14968202	31.1%

Punctuation

Value	Count	Frequency (%)
’	820	30.0%
‘	480	17.6%
“	434	15.9%
”	432	15.8%
	250	9.1%
–	142	5.2%
—	90	3.3%
…	38	1.4%
‑	12	0.4%
‍	7	0.3%
Other values (12)	28	1.0%

None

Value	Count	Frequency (%)
？	213	17.7%
´	192	15.9%
	75	6.2%
，	51	4.2%
ı	46	3.8%
：	40	3.3%
é	35	2.9%
×	31	2.6%
°	29	2.4%
²	19	1.6%
Other values (135)	473	39.3%

Cyrillic

Value	Count	Frequency (%)
С	28	13.1%
о	22	10.3%
а	13	6.1%
в	13	6.1%
н	12	5.6%
е	12	5.6%
к	10	4.7%
с	10	4.7%
т	10	4.7%
и	9	4.2%
Other values (22)	75	35.0%

Currency Symbols

Value	Count	Frequency (%)
€	23	95.8%
₹	1	4.2%

Arrows

Value	Count	Frequency (%)
→	21	91.3%
↓	1	4.3%
↔	1	4.3%

Math Operators

Value	Count	Frequency (%)
−	18	28.1%
≤	11	17.2%
≥	11	17.2%
√	7	10.9%
∑	3	4.7%
∈	3	4.7%
≈	2	3.1%
≠	2	3.1%
∂	2	3.1%
∧	1	1.6%
Other values (4)	4	6.2%

Math Alphanum

Value	Count	Frequency (%)
𝑥	10	20.0%
𝑦	4	8.0%
𝛽	3	6.0%
𝑡	3	6.0%
𝑛	2	4.0%
𝑠	2	4.0%
𝑓	2	4.0%
𝔅	1	2.0%
𝘯	1	2.0%
𝐱	1	2.0%
Other values (21)	21	42.0%

Arabic

Value	Count	Frequency (%)
ه	9	33.3%
؟	7	25.9%
٢	3	11.1%
٠	2	7.4%
ُ	1	3.7%
١	1	3.7%
٥	1	3.7%
٤	1	3.7%
ۜ	1	3.7%
ۣ	1	3.7%

Specials

Value	Count	Frequency (%)
�	9	100.0%

Diacriticals

Value	Count	Frequency (%)
̶	8	38.1%
̃	3	14.3%
̂	2	9.5%
̄	2	9.5%
͡	2	9.5%
̥	1	4.8%
̇	1	4.8%
ͤ	1	4.8%
͜	1	4.8%

Hebrew

Value	Count	Frequency (%)
׳	6	100.0%

Letterlike Symbols

Value	Count	Frequency (%)
ℹ	5	38.5%
™	4	30.8%
ℝ	2	15.4%
№	1	7.7%
Ω	1	7.7%

Hiragana

Value	Count	Frequency (%)
し	4	66.7%
゙	2	33.3%

VS

Value	Count	Frequency (%)
️	3	75.0%
︁	1	25.0%

Devanagari

Value	Count	Frequency (%)
ा	2	13.3%
ि	1	6.7%
व	1	6.7%
क	1	6.7%
ष	1	6.7%
य	1	6.7%
ो	1	6.7%
ं	1	6.7%
ख	1	6.7%
्	1	6.7%
Other values (4)	4	26.7%

Box Drawing

Value	Count	Frequency (%)
│	2	50.0%
╰	1	25.0%
─	1	25.0%

Dingbats

Value	Count	Frequency (%)
✖	2	40.0%
✕	1	20.0%
✘	1	20.0%
➡	1	20.0%

Geometric Shapes

Value	Count	Frequency (%)
▸	2	66.7%
▬	1	33.3%

Katakana

Value	Count	Frequency (%)
・	2	100.0%

Misc Symbols

Value	Count	Frequency (%)
☘	2	66.7%
♣	1	33.3%

Modifier Letters

Value	Count	Frequency (%)
ˆ	2	100.0%

Hangul

Value	Count	Frequency (%)
글	1	50.0%
한	1	50.0%

IPA Ext

Value	Count	Frequency (%)
ɛ	1	25.0%
ɑ	1	25.0%
ɔ	1	25.0%
ɷ	1	25.0%

Emoticons

Value	Count	Frequency (%)
😐	1	100.0%

Block Elements

Value	Count	Frequency (%)
▌	1	100.0%

CJK Compat

Value	Count	Frequency (%)
㎝	1	100.0%

Phonetic Ext

Value	Count	Frequency (%)
ᴛ	1	33.3%
ᴄ	1	33.3%
ᴘ	1	33.3%

Georgian

Value	Count	Frequency (%)
ღ	1	100.0%

Thai

Value	Count	Frequency (%)
็	1	50.0%
๖	1	50.0%

Alphabetic PF

Value	Count	Frequency (%)
ﬁ	1	100.0%

CJK

Value	Count	Frequency (%)
坐	1	25.0%
标	1	25.0%
锛	1	25.0%
稳	1	25.0%

Diacriticals Sup

Value	Count	Frequency (%)
᷿	1	100.0%

Misc Technical

Value	Count	Frequency (%)
⏎	1	100.0%

Tags
Text

Distinct	300067
Distinct (%)	38.2%
Missing	0
Missing (%)	0.0%
Memory size	6.0 MiB

Length

Max length	114
Median length	90
Mean length	30.515018
Min length	3

Characters and Unicode

Total characters	23968204
Distinct characters	42
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	253160 ?
Unique (%)	32.2%

Sample

1st row	<python><reactjs><django><next.js>
2nd row	<python><deep-learning><time-series>
3rd row	<python><tkinter><multiprocessing>
4th row	<python><matplotlib>
5th row	<python><opencv><computer-vision><mask><contour>

Value	Count	Frequency (%)
python	38457	4.9%
python><pandas	19148	2.4%
r	18029	2.3%
python><pandas><dataframe	14100	1.8%
python><python-3.x	8288	1.1%
python><django	6559	0.8%
r><ggplot2	5739	0.7%
python><tkinter	4563	0.6%
r><dplyr	3967	0.5%
python><numpy	3784	0.5%
Other values (300053)	662822	84.4%

Most occurring characters

Value	Count	Frequency (%)
<	2507927	10.5%
>	2507927	10.5%
t	1767767	7.4%
n	1669243	7.0%
o	1663103	6.9%
p	1438458	6.0%
a	1356639	5.7%
e	1187715	5.0%
y	1070383	4.5%
r	1059924	4.4%
Other values (32)	7739118	32.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	18215210	76.0%
Math Symbol	5020723	20.9%
Dash Punctuation	515500	2.2%
Decimal Number	131870	0.6%
Other Punctuation	84901	0.4%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
t	1767767	9.7%
n	1669243	9.2%
o	1663103	9.1%
p	1438458	7.9%
a	1356639	7.4%
e	1187715	6.5%
y	1070383	5.9%
r	1059924	5.8%
h	937994	5.1%
s	932625	5.1%
Other values (16)	5131359	28.2%

Decimal Number

Value	Count	Frequency (%)
3	70789	53.7%
2	31398	23.8%
5	6969	5.3%
1	4702	3.6%
0	4661	3.5%
4	4414	3.3%
7	3007	2.3%
6	2809	2.1%
8	2176	1.7%
9	945	0.7%

Math Symbol

Value	Count	Frequency (%)
<	2507927	50.0%
>	2507927	50.0%
+	4869	0.1%

Other Punctuation

Value	Count	Frequency (%)
.	84107	99.1%
#	794	0.9%

Dash Punctuation

Value	Count	Frequency (%)
-	515500	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	18215210	76.0%
Common	5752994	24.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
t	1767767	9.7%
n	1669243	9.2%
o	1663103	9.1%
p	1438458	7.9%
a	1356639	7.4%
e	1187715	6.5%
y	1070383	5.9%
r	1059924	5.8%
h	937994	5.1%
s	932625	5.1%
Other values (16)	5131359	28.2%

Common

Value	Count	Frequency (%)
<	2507927	43.6%
>	2507927	43.6%
-	515500	9.0%
.	84107	1.5%
3	70789	1.2%
2	31398	0.5%
5	6969	0.1%
+	4869	0.1%
1	4702	0.1%
0	4661	0.1%
Other values (6)	14145	0.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	23968204	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
<	2507927	10.5%
>	2507927	10.5%
t	1767767	7.4%
n	1669243	7.0%
o	1663103	6.9%
p	1438458	6.0%
a	1356639	5.7%
e	1187715	5.0%
y	1070383	4.5%
r	1059924	4.4%
Other values (32)	7739118	32.3%

CommentCount
Real number (ℝ)

ZEROS

Distinct	45
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.9042862

Minimum	0
Maximum	62
Zeros	302229
Zeros (%)	38.5%
Negative	0
Negative (%)	0.0%
Memory size	6.0 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1
Q3	3
95-th percentile	7
Maximum	62
Range	62
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	2.431166
Coefficient of variation (CV)	1.276681
Kurtosis	10.163676
Mean	1.9042862
Median Absolute Deviation (MAD)	1
Skewness	2.3039242
Sum	1495733
Variance	5.9105682
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=45)

Value	Count	Frequency (%)
0	302229	38.5%
2	128241	16.3%
1	128029	16.3%
3	79190	10.1%
4	53287	6.8%
5	32806	4.2%
6	21466	2.7%
7	13375	1.7%
8	8966	1.1%
9	5724	0.7%
Other values (35)	12143	1.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	302229	38.5%
1	128029	16.3%
2	128241	16.3%
3	79190	10.1%
4	53287	6.8%
5	32806	4.2%
6	21466	2.7%
7	13375	1.7%
8	8966	1.1%
9	5724	0.7%

Value	Count	Frequency (%)
62	1	< 0.1%
61	1	< 0.1%
46	1	< 0.1%
44	1	< 0.1%
43	1	< 0.1%
42	2	< 0.1%
39	1	< 0.1%
38	2	< 0.1%
37	1	< 0.1%
36	1	< 0.1%

OwnerDisplayName
Text

MISSING

Distinct	5217
Distinct (%)	38.8%
Missing	772004
Missing (%)	98.3%
Memory size	6.0 MiB

Length

Max length	24
Median length	12
Mean length	11.814451
Min length	3

Characters and Unicode

Total characters	158928
Distinct characters	93
Distinct categories	7 ?
Distinct scripts	4 ?
Distinct blocks	3 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2945 ?
Unique (%)	21.9%

Sample

1st row	Joe
2nd row	not_a_generic_user
3rd row	user20775003
4th row	Korodoro
5th row	Dan Swogger

Value	Count	Frequency (%)
user16774617	80	0.6%
user12314098	73	0.5%
user2110417	71	0.5%
anon	52	0.4%
user18948933	50	0.4%
user13467695	49	0.4%
user18313765	44	0.3%
user17582908	39	0.3%
user7864386	39	0.3%
user14251114	37	0.3%
Other values (5321)	13061	96.1%

Most occurring characters

Value	Count	Frequency (%)
1	19462	12.2%
e	13288	8.4%
r	13225	8.3%
s	13192	8.3%
u	13119	8.3%
4	10210	6.4%
5	10026	6.3%
6	9628	6.1%
2	9430	5.9%
7	9301	5.9%
Other values (83)	38047	23.9%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	103432	65.1%
Lowercase Letter	54878	34.5%
Uppercase Letter	439	0.3%
Space Separator	143	0.1%
Other Punctuation	17	< 0.1%
Connector Punctuation	14	< 0.1%
Dash Punctuation	5	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	13288	24.2%
r	13225	24.1%
s	13192	24.0%
u	13119	23.9%
a	369	0.7%
n	311	0.6%
o	222	0.4%
i	215	0.4%
l	137	0.2%
t	118	0.2%
Other values (39)	682	1.2%

Uppercase Letter

Value	Count	Frequency (%)
S	44	10.0%
A	41	9.3%
M	33	7.5%
D	32	7.3%
C	28	6.4%
P	27	6.2%
J	24	5.5%
R	23	5.2%
B	22	5.0%
H	20	4.6%
Other values (19)	145	33.0%

Decimal Number

Value	Count	Frequency (%)
1	19462	18.8%
4	10210	9.9%
5	10026	9.7%
6	9628	9.3%
2	9430	9.1%
7	9301	9.0%
9	9169	8.9%
3	8871	8.6%
8	8805	8.5%
0	8530	8.2%

Other Punctuation

Value	Count	Frequency (%)
.	15	88.2%
'	2	11.8%

Space Separator

Value	Count	Frequency (%)
	143	100.0%

Connector Punctuation

Value	Count	Frequency (%)
_	14	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	5	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	103611	65.2%
Latin	55290	34.8%
Cyrillic	16	< 0.1%
Greek	11	< 0.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	13288	24.0%
r	13225	23.9%
s	13192	23.9%
u	13119	23.7%
a	369	0.7%
n	311	0.6%
o	222	0.4%
i	215	0.4%
l	137	0.2%
t	118	0.2%
Other values (46)	1094	2.0%

Common

Value	Count	Frequency (%)
1	19462	18.8%
4	10210	9.9%
5	10026	9.7%
6	9628	9.3%
2	9430	9.1%
7	9301	9.0%
9	9169	8.8%
3	8871	8.6%
8	8805	8.5%
0	8530	8.2%
Other values (5)	179	0.2%

Cyrillic

Value	Count	Frequency (%)
и	2	12.5%
е	2	12.5%
р	2	12.5%
л	1	6.2%
б	1	6.2%
К	1	6.2%
й	1	6.2%
т	1	6.2%
н	1	6.2%
в	1	6.2%
Other values (3)	3	18.8%

Greek

Value	Count	Frequency (%)
α	2	18.2%
ς	2	18.2%
δ	1	9.1%
ύ	1	9.1%
ο	1	9.1%
Κ	1	9.1%
τ	1	9.1%
σ	1	9.1%
ώ	1	9.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	158897	> 99.9%
Cyrillic	16	< 0.1%
None	15	< 0.1%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	19462	12.2%
e	13288	8.4%
r	13225	8.3%
s	13192	8.3%
u	13119	8.3%
4	10210	6.4%
5	10026	6.3%
6	9628	6.1%
2	9430	5.9%
7	9301	5.9%
Other values (57)	38016	23.9%

Cyrillic

Value	Count	Frequency (%)
и	2	12.5%
е	2	12.5%
р	2	12.5%
л	1	6.2%
б	1	6.2%
К	1	6.2%
й	1	6.2%
т	1	6.2%
н	1	6.2%
в	1	6.2%
Other values (3)	3	18.8%

None

Value	Count	Frequency (%)
α	2	13.3%
ς	2	13.3%
é	1	6.7%
á	1	6.7%
δ	1	6.7%
ύ	1	6.7%
ο	1	6.7%
Κ	1	6.7%
í	1	6.7%
ö	1	6.7%
Other values (3)	3	20.0%

LastEditDate
Date

MISSING

Distinct	409200
Distinct (%)	99.7%
Missing	374977
Missing (%)	47.7%
Memory size	6.0 MiB

Minimum	2020-11-01 00:27:27
Maximum	2023-10-08 09:18:34

Histogram

Histogram with fixed size bins (bins=50)

LastActivityDate
Date

Distinct	781582
Distinct (%)	99.5%
Missing	0
Missing (%)	0.0%
Memory size	6.0 MiB

Minimum	2020-11-01 00:03:26
Maximum	2023-10-08 09:40:17

Histogram

Histogram with fixed size bins (bins=50)

Auto

Heatmap
Table

	Unnamed: 0	Id	Score	ViewCount	AnswerCount	CommentCount
Unnamed: 0	1.000	-0.010	-0.018	0.030	-0.000	0.013
Id	-0.010	1.000	-0.099	-0.369	-0.153	-0.032
Score	-0.018	-0.099	1.000	0.247	0.075	-0.121
ViewCount	0.030	-0.369	0.247	1.000	0.233	0.013
AnswerCount	-0.000	-0.153	0.075	0.233	1.000	-0.149
CommentCount	0.013	-0.032	-0.121	0.013	-0.149	1.000

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

First rows
Last rows

	Unnamed: 0	Id	CreationDate	Score	ViewCount	AnswerCount	Title	Tags	CommentCount	OwnerDisplayName	LastEditDate	LastActivityDate
0	47323	77253066	2023-10-08 09:37:48	0	5	0	How to solve create next app npm run build placing href with _next instead of .next in the html files from the server?	<python><reactjs><django><next.js>	0	NaN	NaN	2023-10-08 09:37:48
1	47322	77253065	2023-10-08 09:37:34	0	3	0	Time series prediction code fails to run in an iterative loop, but works when run out of loop	<python><deep-learning><time-series>	0	NaN	NaN	2023-10-08 09:37:34
2	47321	77253053	2023-10-08 09:33:04	0	8	0	Two way communication between two Processes python	<python><tkinter><multiprocessing>	0	NaN	NaN	2023-10-08 09:33:04
3	47320	77253022	2023-10-08 09:23:00	0	10	1	Plotting with subplots in a loop in one figure	<python><matplotlib>	0	NaN	NaN	2023-10-08 09:37:31
4	47319	77253020	2023-10-08 09:22:32	0	6	0	Adjust the edge points of a rectangular shaped contour	<python><opencv><computer-vision><mask><contour>	0	NaN	NaN	2023-10-08 09:22:32
5	47318	77253005	2023-10-08 09:17:09	0	5	0	builtins.AttributeError: 'sqlite3.Connection' object has no attribute 'enable_load_extension'	<python><python-3.x><sqlite><python-3.6><python-venv>	0	NaN	NaN	2023-10-08 09:17:09
6	47317	77252991	2023-10-08 09:13:06	0	7	0	Sending `multipart/form-data` to AWS Lambda emulator locally	<python><amazon-web-services><docker><aws-lambda><multipartform-data>	0	NaN	2023-10-08 09:18:29	2023-10-08 09:18:29
7	47316	77252989	2023-10-08 09:12:33	0	7	0	I used Dask to read my 7gb CSV but now there is an error	<python><dask>	1	NaN	NaN	2023-10-08 09:12:33
8	47315	77252967	2023-10-08 09:04:47	-1	7	0	can i use trapezium bounding boxing in yolov7 instead of rectangle bonding boxes	<python><computer-vision><object-detection><yolov7>	0	NaN	NaN	2023-10-08 09:04:47
9	47314	77252952	2023-10-08 09:00:53	-2	9	0	How to copy a table and insert it behind the original table?	<python><docx>	0	NaN	NaN	2023-10-08 09:00:53

	Unnamed: 0	Id	CreationDate	Score	ViewCount	AnswerCount	Title	Tags	CommentCount	OwnerDisplayName	LastEditDate	LastActivityDate
785446	43764	73186067	2022-07-31 18:48:45	2	328	2	Change colour of geom_point for maximum y value	<r><ggplot2><data-visualization><geom-point>	2	NaN	2022-07-31 19:12:38	2022-07-31 19:12:38
785447	43765	73186087	2022-07-31 18:50:31	0	62	0	R: Propensity score with matchit package for data with variables specific to subgroups	<r><propensity-score-matching>	2	NaN	NaN	2023-06-11 15:00:25
785448	43766	73186091	2022-07-31 18:50:46	2	272	1	Connecting R Shiny to R Script with Function	<r><shiny>	6	NaN	2022-08-01 02:45:16	2022-08-01 02:56:16
785449	43767	73187123	2022-07-31 21:45:26	0	68	1	How to get _FILE_ macro enabled using Rcpp?	<c++><r><file><imagemagick><rcpp>	7	NaN	2023-03-10 21:47:43	2023-03-10 21:47:43
785450	43768	73187330	2022-07-31 22:24:32	0	137	1	Not automatically downloading dropbox files when opening data in R	<r><synchronization><dropbox>	2	NaN	2022-07-31 22:54:07	2022-08-01 21:03:44
785451	43769	73187339	2022-07-31 22:26:03	4	462	1	Can I apply styling to inline code in an R Notebook?	<r><r-markdown><rnotebook><inline-code>	1	NaN	2022-08-02 21:44:11	2022-08-02 21:44:11
785452	43770	73187426	2022-07-31 22:45:59	1	25	1	Windows Rstudio 4.1.2 and neo4r_0.1.1 connection problem	<r><neo4r>	0	NaN	NaN	2022-08-02 01:08:55
785453	43791	73186766	2022-07-31 20:40:48	0	139	2	Filter rows that are matched on multiple conditions	<r><dataframe><dplyr><data.table><stringr>	0	NaN	2022-07-31 22:34:41	2022-07-31 23:15:08
785454	43792	73186786	2022-07-31 20:46:12	1	199	3	Sample Multiple Columns Without Repeats R dplyr	<r><random><dplyr><probability><sample>	1	NaN	NaN	2022-07-31 23:57:26
785455	43864	73327634	2022-07-27 19:56:28	1	16	2	Comparing function to variable in R	<r><dplyr>	0	Eisen	NaN	2022-08-11 22:59:05

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Other Punctuation

Math Symbol

Other Symbol

Nonspacing Mark

Other Letter

Decimal Number

Open Punctuation

Close Punctuation

Currency Symbol

Other Number

Dash Punctuation

Space Separator

Modifier Symbol

Final Punctuation

Initial Punctuation

Format

Spacing Mark

Modifier Letter

Private Use

Connector Punctuation

Control

Enclosing Mark

Line Separator

Most occurring scripts

Most frequent character per script

Common

Latin

Cyrillic

Greek

Inherited

Devanagari

Arabic

Han

Hangul

Thai

Unknown

Hebrew

Hiragana

Georgian

Most occurring blocks

Most frequent character per block

ASCII

Punctuation

None

Cyrillic

Currency Symbols

Arrows

Math Operators

Math Alphanum

Arabic

Specials

Diacriticals

Hebrew

Letterlike Symbols

Hiragana

VS

Devanagari

Box Drawing

Dingbats

Geometric Shapes

Katakana

Misc Symbols

Modifier Letters

Hangul

IPA Ext

Emoticons

Block Elements

CJK Compat

Phonetic Ext

Georgian

Thai

Alphabetic PF

CJK